DBMS > Amazon DynamoDB vs. Kyligence Enterprise vs. MarkLogic vs. Microsoft Azure Table Storage vs. Warp 10

System Properties Comparison Amazon DynamoDB vs. Kyligence Enterprise vs. MarkLogic vs. Microsoft Azure Table Storage vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

A distributed analytics engine for big data, built on top of Apache Kylin

Operational and transactional Enterprise NoSQL database

A Wide Column Store for rapid development using massive semi-structured datasets

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Document store
Key-value store

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Wide column store

Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.46
Rank	#266	Overall
	#124	Relational DBMS

Score	5.18
Rank	#63	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#7	Search engines

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

aws.amazon.com/dynamodb

kyligence.io/kyligence-enterprise

www.progress.com/marklogic

azure.microsoft.com/en-us/services/storage/tables

www.warp10.io

Technical documentation

docs.aws.amazon.com/dynamodb

www.progress.com/marklogic/documentation

www.warp10.io/content/02_Getting_started

Developer

Amazon

Kyligence, Inc.

MarkLogic Corp.

Microsoft

SenX

Initial release

2012

2016

2001

2012

2015

Current release

11.0, December 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

restricted free version is available

commercial

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Java

Server operating systems

hosted

Linux

Linux
OS X
Windows

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Schema can be enforced

schema-free

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

SQL92

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

RESTful HTTP API

HTTP API
Jupyter
WebSocket

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

yes

WarpScript

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

ACID across one or more tables within a single AWS account and region

ACID

can act as a resource manager in an XA/JTA transaction

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, with Range Indexes

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Role-based access control at the document and subdocument levels

Access rights based on private key authentication or shared access signatures

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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